Variations in MRI acquisition protocols and machinery result in different appearances of tissue in acquired image data. Image intensities in MRI do not have a fixed meaning, even within the same protocol for the same body region obtained on the same scanner for the same patient. The variations between scans, scanner, protocols, etc. present issues in image display, segmentation, and quantification.
For example, for an MRI scan of the brain, preprocessing enables extraction of the brain and its main tissues. Several approaches address extraction of the brain and brain tissues. Methods such as boundary region based, atlas based, and machine learning based segmentation approaches have been used. However, the results are often unequal due to the variations in acquired data, for example, a level of brightness or color depending on the sequence and the protocol the input data was acquired in. In an example, the results of segmentation by two physicians may differ because of the differences in the physician's training in MRI data acquisition. Different machines, different sequences, or different settings may provide different intensities. Different environmental conditions may lead to different results even from the same machine or patient from scan to scan.